Spatial Normalization in Voxel-Wise Analysis of FDG-PET Brain Images

摘要

Spatial normalization is a preliminary step in any PET image analysis based on statistical parametric mapping (SPM). This step consists in applying a spatial deformation to match each PET scan to an anatomical reference template The purpose of this study was to evaluate the effect of using different methods of spatial normalization on the results of SPM analysis of 18F-FDG PET images by comparing controls and patients diagnosed with mild cognitive impairment (MCI) that converted to probable Alzheimer's disease (AD) after two years of follow-up. We performed an SPM analysis between the two groups using three spatial normalization methods: 1) MRI-DARTEL 2) MRI-SPM8 and 3) FDG-SPM8. MRI-DARTEL and MRI-SPM8 combine structural and functional images, while FDG-SPM8 is based only on functional images. The results obtained with the three methods were consistent in terms of the pattern of hypometabolism detected in the patient group. However, MRI-DARTEL was the method more consistent with the patterns previously reported in the literature. These results suggest that MRI-DARTEL is the most accurate and powerful method for spatial normalization in SPM analysis of 18F-FDG PET images. Normalization based solely on functional imaging shows less sensitivity to detect significant differences.